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Online Learning

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SPSP provides online professional development to members at all career stages. Some of these opportunities are offered live and made available in recorded format, while others are only in video format.

Check back soon for upcoming Online Training opportunities.

Non-academic Careers: Is a Non-academic Life for Me?

Lily Jampol headshot

Lily Jampol
People Scientist & D&I Strategist at ReadySet

Paul Litvak headshot

Paul Litvak
Product Manager at Airbnb


You are curious about a non-academic career, but don't know if it's for you. Nearly everyone who has transitioned out of academia has gone through some soul searching before taking the plunge, so you are not alone. Dr. Lily Jampol (People Scientist & D&I Strategist at ReadySet) and Dr. Paul Litvak (Product Manager at Airbnb) discuss how they made the decision to start a new journey. They touch on several precursors to making this decision, including:

  • How do we even know what it is we want?
  • How sure do you have to be to make the decision to leave academia?
  • What factors to think about when evaluating career paths
  • How to get information on specific jobs and career paths

September 25, 2019


Applying for Positions at Teaching-Focused Institutions

Leslie Zorwick headshot

Leslie Zorwick
Hendrix College

Alicia Nordstrom headshot

Alicia Nordstrom
Misericordia University

Carrie Langner headshot

Carrie Langner
California State Polytechnic University

Camille Johnson headshot

Camille Johnson (moderator)
San Jose State University


Because we all go to graduate school at PhD granting institutions, we may be less familiar with the working of non-PhD granting institutions and how to successfully apply to jobs at such institutions. While a record of research productivity remains important, other aspects of application packages are equally important – including diversity statements, teaching portfolios, and how research is talked about. Three panelists from institutions at teaching-focused institutions (i.e. small liberal arts and master's granting) talk about how to convey your interests, skills, and expertise through a well-crafted cover letter, CV, research statement, diversity and inclusion statement, and teaching statement. They also describe the recruiting process and what they look for in candidates.

July 30, 2019


Theory and Practice of Bayesian Inference Using JASP

Alexander Etz headshot

Alexander Etz
University of California, Irvine

Julia Haaf headshot

Julia Haaf
University of Amsterdam

Johnny van Doorn headshot

Johnny van Doorn
University of Amsterdam

This webinar provides attendees with a friendly, gentle introduction to Bayesian statistics, and demonstrates how to perform Bayesian analyses using JASP statistical software. Attendees will come away understanding the "why" and "how" of Bayesian estimation and hypothesis testing. This workshop is relevant to any student or researcher who wishes to draw conclusions from empirical data. No background in Bayesian statistics is required.

June 21, 2019


Turning your CV into a Résumé

David A. Richards

This conversational webinar leads attendees through the process of turning a curriculum vitae into a résumé suitable for seeking employment outside academia. Discussion topics will include the differences between a CV and a résumé, and the process of developing the former into the latter. Practical, specific tips will be provided throughout.

The intended audience for this webinar is current graduate students, as well as recent graduate students who are early in their career since earning a graduate degree, but it may be of interest to any trained academic interested in pursuing a career outside the ivory tower.

May 21, 2019


Creating Reproducible Research Reports Using R Markdown

Michael Frank headshot

Michael Frank

Stanford University

R Markdown is a simple but very powerful way to mix R data analysis code and text. R Markdown documents are a great way to document your data analysis and create reproducible reports (e.g., that automatically render your graphs and tables and even your results section from your data). You can even use R Markdown to write your entire paper, avoiding copy-and-pasting your analyses, which can be a major source of errors in papers. The rendered documents look spiffy on the web and in print. In this workshop, we introduce R Markdown and show how it can be used as part of a reproducible writing workflow.

December 5, 2018


A Practical Guide to Multilevel Modeling: Part 2

Amie Gordon headshot

Amie M. Gordon (email)
University of California San Francisco

This is the second of a two-part multilevel modeling (MLM) webinar for newbies as well as researchers who have been exposed to it through a prior class or workshop but still have lots of questions. Topics in Part 2 include: 

1. Fixed versus random effects – the difference between fixed and random effects and what changes in the analysis process when random slopes are allowed in the model.

2. Grand-mean versus group centering – what they are and when to use them, unconfounding within and between person effects.

3. Covariance matrices – cover the basics of the residual and random effects covariance matrices.

September 27, 2018


A Practical Guide to Multilevel Modeling: Part 1

Amie Gordon headshot

Amie M. Gordon (email)
University of California San Francisco

This is the first of a two-part multilevel modeling (MLM) webinar for newbies as well as researchers who have been exposed to it through a prior class or workshop but still have lots of questions. Topics in Part 1 include: 

1. Identifying if MLM is necessary – the first step in MLM is figuring out whether data actually violates assumptions of independence.

2. Figuring out the nested structure of your data (including cross-classified models) – Identifying the sources of non-independence in your data, including the possibility of cross-classification.

3. Approaches to dealing with non-independence – when to deal with non-independence through random versus fixed factors.

September 26, 2018


Introduction to R

This eight-part video series provides an applied introduction to R for new users.